A better environment through better terology

A better environment can be achieved through the reduced emission of pollutants, the optimization of green energy production and the optimization of maintenance interventions, which is an important contribution in getting equipment functioning as efficiently and effectively as possible and, of no less importance, to minimize the downtime caused by faults. These are the key points presented in this paper, which also emphasizes the very recent contribution of 3D models in aiding fault diagnosis and terology in general. The way to achieve the above-mentioned objectives is through on-condition maintenance in two main fields, wind farms and Diesel engines. In wind farms, maintenance is done through the control of variables, such as vibration signals and the balance of electrical currents. As for Diesel engines, on-condition variables are the emissions of PM10, NOx, CO, HC and CO2. However, there are problems in both situations, namely, in the first case, the distance and accessibility of the generators and, in the second case, the problems associated with the fact that the equipment is not static. Another common problem in both situations is the measuring and transmission of the values of the on-condition variables, because, in the case of wind farms, the machine is placed on top of the tower and, in the case of Diesel engines, the vehicles are in operation most of the time and most of the measurements need be made while the vehicles are running. Also, although the two situations seem different, they have many issues in common, such as those above-mentioned, for which we will propose convergent solutions that have an Integrated Modular System for Terology (SMIT - Sistema Modular Integrado de Terologia) as a base platform. In addition, to collect, transmit and manage data, we also propose low-cost hardware devices and open-source software, with time series, Hidden Markov Models and genetic algorithms incorporated into them, to enable the prediction of new maintenance interventions. Another important development that is mentioned, with the objective of achieving a more effective terology system, is the implementation of 3D models to aid fault diagnosis and maintenance interventions in general. All these subjects are treated in this paper in a cohesive and synergistic way in order to achieve more effective terology management with an environmental perspective.